Tropical forest disaster monitoring with multi-scale sensors from terrestrial laser, UAV, to satellite radar

Forest disaster monitoring requires frequent data observation of remotely sensed data. It is getting more common to use open satellite image archives to monitor land use change from multi-temporal data. In this study, multi-temporal DSM created by UAV-SfM is used to identify forest gap. ALOS 2 full polarization data is compared with the finer scale height difference detected by multi-temporal UAV based DSMs. Advantage of UAV based observation is to identify forest gap area efficiently in wide area and collect more samples to compare wide coverage of the satellite radar backscatter to understand backscatter characteristics. As a result, HH and HV polarization has detection power of forest gap size.